Question
Full-time
5-10

Machine Learning Engineer

12/7/2025

Lead the design and implementation of advanced machine learning algorithms to solve complex problems in a customer-facing environment. Collaborate closely with data engineers, product managers, and domain experts to operationalize machine learning models into production.

Working Hours

40 hours/week

Company Size

201-500 employees

Language

English

Visa Sponsorship

No

About The Company
LSports aspires to lead the sports data industry by creating unique technologies in order to provide business advantages to our partners. Using our advanced sports technology, we collect and process enormous amounts of sports data in real-time. AI, ML, and CV are only some of the mechanics used to create the fastest and most trustworthy database, ultimately sent to our partners. We’re here to meet your needs. Creating innovative solutions to suit our partners' requirements is our main goal at LSports. We focus on making customizable and personalized services that will offer the best products possible.
About the Role

LSports is a world-leading sports data provider, trusted by sportsbooks worldwide to deliver real-time data with unmatched accuracy and reliability. With technology that drives smarter trading and deeper engagement, we empower bookmakers to grow, innovate, and stay ahead of the game.

If you’re passionate about sports and technology and want to make your mark in a fast-moving industry, don't miss this chance! Step onto the field with us and help build the future of sports data – We are looking for a talented Machine Learning Engineer.

About the team: Trade360

Trade360 group is the powerhouse behind LSports' exceptional portfolio of customer-facing products, blending innovation, functionality, and user experience to deliver industry-leading solutions that redefine customer engagement and satisfaction.

Responsibilities:

  • Lead the design and implementation of advanced machine learning algorithms to solve complex problems in a customer facing environment.
  • Collaborate closely with data engineers, product managers and domain experts to operationalize machine learning models into production.
  • Evaluate the effectiveness of machine learning models through comprehensive validation metrics and make iterative improvements.
  • Conduct research to keep abreast of the latest advancements in machine learning and artificial intelligence.

Requirements

  • 5+ years of experience in machine learning or data science, with a proven track record of deploying machine learning models into production.
  • Proficiency in Python and machine learning frameworks like PyTorch, or scikit-learn.
  • Strong understanding of algorithms, data structures, and statistical modeling techniques.
  • Product oriented - proven experience with ML PoCs / MVP from ideation to execution.
  • Experience with SQL and NoSQL Databases.
  • Experience with Databricks or similar.
  • Proven experience in Risk and Fraud AI products.

Advantages

  • MLOps experience.
  • Experience with Kafka.
  • Experience with building GenAI applications.

Life at LSports

We’re honest with each other and open to new ideas. We challenge ourselves to excel, knowing that good relationships never come at the expense of professionalism. We’re dynamic, always growing and improving to stay on top.

Come join a team that’s all about winning together, with integrity and heart.


All the Extras You Deserve

  • Health insurance
  • Professional development with skills-based courses
  • Hybrid work model (Wallaballa)
  • Cibus
  • Birthday day off
  • Access to ‘Group Hug’ platform
  • Fun company and team social events
  • Kids Summer Camp


Key Skills
Machine LearningData SciencePythonPyTorchScikit-learnAlgorithmsData StructuresStatistical ModelingSQLNoSQLDatabricksRisk AIFraud AIMLOpsKafkaGenAI
Categories
TechnologyData & AnalyticsEngineeringSports & Recreation
Benefits
Health InsuranceProfessional DevelopmentHybrid Work ModelBirthday Day OffAccess to ‘Group Hug’ PlatformFun Company and Team Social EventsKids Summer Camp
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